def test_check_network_health_one_isolated_cluster(self):
net = op.network.Cubic(shape=[5, 5, 5])
Ps = net['pore.coords'][:, 2] == 2.5
Ps = Ps * (net['pore.coords'][:, 1] > 2.5)
Ts = net.find_neighbor_throats(pores=Ps, mode='exclusive_or')
trim(network=net, throats=Ts)
a = net.project.check_network_health()
assert len(a['disconnected_pores']) == 10
def test_check_network_health_one_isolated_cluster(self):
net = op.network.Cubic(shape=[5, 5, 5])
Ps = net['pore.coords'][:, 2] == 2.5
Ps = Ps*(net['pore.coords'][:, 1] > 2.5)
Ts = net.find_neighbor_throats(pores=Ps, mode='exclusive_or')
trim(network=net, throats=Ts)
a = net.check_network_health()
assert len(a['disconnected_clusters']) == 2
assert len(a['trim_pores']) == 10
def __init__(self, shape=[1, 1, 1], points=None, **kwargs):
# Clean-up input points
points = self._parse_points(shape=shape, points=points)
super().__init__(shape=shape, points=points, **kwargs)
# Initialize network object
topotools.trim(network=self, pores=self.pores('delaunay'))
pop = ['pore.delaunay', 'throat.delaunay', 'throat.interconnect']
for item in pop:
del self[item]
def test_check_network_health_isolated_pores(self):
net = op.network.Cubic(shape=[5, 5, 5])
Ts = net.find_neighbor_throats(pores=0)
trim(network=net, throats=Ts)
a = net.check_network_health()
assert a['isolated_pores'] == np.array([0])
trim(network=net, pores=a['trim_pores'])
a = net.check_network_health()
assert np.size(a['isolated_pores']) == 0
def __init__(self, template, spacing=[1, 1, 1], **kwargs):
template = sp.atleast_3d(template)
super().__init__(shape=template.shape, **kwargs)
coords = sp.unravel_index(range(template.size), template.shape)
self['pore.template_coords'] = sp.vstack(coords).T
self['pore.template_indices'] = self.Ps
self['pore.drop'] = template.flatten() == 0
topotools.trim(network=self, pores=self.pores('drop'))
del self['pore.drop']
def __init__(self, shape=None, num_points=None, **kwargs):
# Clean-up input points
points = kwargs.pop('points', None)
points = self._parse_points(shape=shape,
num_points=num_points,
points=points)
# Initialize network object
super().__init__(shape=shape, points=points, **kwargs)
topotools.trim(network=self, pores=self.pores('delaunay'))
pop = ['pore.delaunay', 'throat.delaunay', 'throat.interconnect']
for item in pop:
del self[item]
def __init__(self,
num_points=None,
points=None,
shape=[1, 1, 1],
fiber_rad=None,
resolution=1e-2,
name=None,
**kwargs):
super().__init__(name=name)
shape = np.array(shape)
if (len(shape) != 3) or np.any(shape == 0):
raise Exception('Only 3D, rectangular shapes are supported')
if fiber_rad is None:
logger.exception(msg='Please initialize class with a fiber_rad')
net = DelaunayVoronoiDual(project=self,
num_points=num_points,
points=points,
shape=shape,
name=self.name + '_net',
**kwargs)
net.fiber_rad = fiber_rad
net.resolution = resolution
del_geom = DelaunayGeometry(project=self,
network=net,
pores=net.pores('delaunay'),
throats=net.throats('delaunay'),
name=self.name + '_del')
VoronoiGeometry(project=self,
network=net,
pores=net.pores('voronoi'),
throats=net.throats('voronoi'),
name=self.name + '_vor')
# Tidy up network
h = net.check_network_health()
if len(h['trim_pores']) > 0:
topotools.trim(network=net, pores=h['trim_pores'])
# Copy the Delaunay throat diameters to the boundary pores
Ps = net.pores(['delaunay', 'boundary'], mode='xnor')
map_Ps = del_geom.map_pores(pores=Ps, origin=net)
all_Ts = net.find_neighbor_throats(pores=Ps, flatten=False)
for i, Ts in enumerate(all_Ts):
Ts = np.asarray(Ts)
Ts = Ts[net['throat.delaunay'][Ts]]
if len(Ts) > 0:
map_Ts = del_geom.map_throats(throats=Ts, origin=net)
td = del_geom['throat.diameter'][map_Ts]
ta = del_geom['throat.area'][map_Ts]
del_geom['pore.diameter'][map_Ps[i]] = td
del_geom['pore.area'][map_Ps[i]] = ta
del_geom.regenerate_models(propnames=['throat.equivalent_area'])
def test_trim_throats(self):
np.random.seed(1)
pn = op.network.Cubic(shape=[2, 2, 2], spacing=5)
Ps = pn.pores()[:4]
Ts1 = pn.find_neighbor_throats(pores=Ps, mode='or')
geo1 = op.geometry.GenericGeometry(network=pn, pores=Ps, throats=Ts1)
Ps = pn.pores()[4:]
Ts2 = pn.find_neighbor_throats(pores=Ps, mode='xnor')
geo2 = op.geometry.GenericGeometry(network=pn, pores=Ps, throats=Ts2)
geo1['throat.random'] = np.random.random(geo1.Nt)
geo2['throat.random'] = np.random.random(geo2.Nt)
trimmers = pn['throat.random'] < 0.25
topotools.trim(pn, throats=pn.throats()[trimmers])
assert ~np.any(pn['throat.random'] < 0.25)
def test_trim_throats(self):
np.random.seed(1)
pn = op.network.Cubic(shape=[2, 2, 2], spacing=5)
Ps = pn.pores()[:4]
Ts1 = pn.find_neighbor_throats(pores=Ps, mode='or')
geo1 = op.geometry.GenericGeometry(network=pn, pores=Ps, throats=Ts1)
Ps = pn.pores()[4:]
Ts2 = pn.find_neighbor_throats(pores=Ps, mode='xnor')
geo2 = op.geometry.GenericGeometry(network=pn, pores=Ps, throats=Ts2)
geo1['throat.random'] = np.random.random(geo1.Nt)
geo2['throat.random'] = np.random.random(geo2.Nt)
trimmers = pn['throat.random'] < 0.25
topotools.trim(pn, throats=pn.throats()[trimmers])
assert ~np.any(pn['throat.random'] < 0.25)
def __init__(self, template, spacing=[1, 1, 1], **kwargs):
template = np.atleast_3d(template)
super().__init__(shape=template.shape, spacing=spacing, **kwargs)
coords = np.unravel_index(range(template.size), template.shape)
self['pore.template_coords'] = np.vstack(coords).T
self['pore.template_indices'] = self.Ps
topotools.trim(network=self, pores=template.flatten() == 0)
# Add "internal_surface" label to "fake" surface pores!
ndims = topotools.dimensionality(self).sum()
max_neighbors = 6 if ndims == 3 else 4
num_neighbors = np.diff(self.get_adjacency_matrix(fmt="csr").indptr)
mask_surface = self["pore.surface"]
mask_internal_surface = (num_neighbors < max_neighbors) & ~mask_surface
self.set_label("pore.internal_surface", pores=mask_internal_surface)
def test_check_network_health_isolated_pores_and_clusters(self):
net = op.network.Cubic(shape=[5, 5, 5])
# Create first isolated cluster
Ps = net['pore.coords'][:, 2] == 2.5
Ps = Ps * (net['pore.coords'][:, 1] > 2.5)
Ts = net.find_neighbor_throats(pores=Ps, mode='exclusive_or')
trim(network=net, throats=Ts)
# Create an isolated pore
Ts = net.find_neighbor_throats(pores=0)
trim(network=net, throats=Ts)
a = net.check_network_health()
# Ensure trim_pores has right length
assert len(a['disconnected_pores']) == 11
# Ensure 0 is listed in trim pores
assert 0 in a['disconnected_pores']
def test_check_network_health_two_isolated_clusters(self):
net = op.network.Cubic(shape=[5, 5, 5])
# Create first isolated cluster
Ps = net['pore.coords'][:, 2] == 2.5
Ps = Ps*(net['pore.coords'][:, 1] > 2.5)
Ts = net.find_neighbor_throats(pores=Ps, mode='exclusive_or')
trim(network=net, throats=Ts)
# Create a second isolated cluster
Ps = net['pore.coords'][:, 2] == 3.5
Ps = Ps*(net['pore.coords'][:, 1] < 2.5)
Ts = net.find_neighbor_throats(pores=Ps, mode='exclusive_or')
trim(network=net, throats=Ts)
a = net.check_network_health()
assert len(a['disconnected_clusters']) == 3
assert len(a['trim_pores']) == 20
def __init__(self, shape=[1, 1, 1], num_points=None, points=None, **kwargs):
# Clean-up input points
points = self._parse_points(shape=shape,
num_points=num_points,
points=points)
super().__init__(shape=shape, points=points, **kwargs)
# Initialize network object
topotools.trim(network=self, pores=self.pores(['voronoi']))
pop = ['pore.voronoi', 'throat.voronoi', 'throat.interconnect',
'pore.delaunay', 'throat.delaunay']
for item in pop:
del self[item]
# Trim additional pores that are missed by the parent class's trimming
Ps = topotools.isoutside(coords=self['pore.coords'], shape=shape)
topotools.trim(network=self, pores=Ps)
def __init__(self, shape, num_points=None, **kwargs):
# Generate Delaunay tessellation from super class, then trim
super().__init__(shape=shape, num_points=num_points, **kwargs)
points = self['pore.coords']
conns = self['throat.conns']
# Find centroid of each pair of nodes
c = points[conns]
m = (c[:, 0, :] + c[:, 1, :]) / 2
# Find radius of circle connecting each pair of nodes
r = np.sqrt(np.sum((c[:, 0, :] - c[:, 1, :])**2, axis=1)) / 2
# Use KD-Tree to find distance to nearest neighbors
tree = sptl.cKDTree(points)
n = tree.query(x=m, k=1)[0]
# Identify throats whose centroid is not near an unconnected node
g = np.around(n, decimals=5) == np.around(r, decimals=5)
trim(self, throats=~g)
def __init__(self, shape, num_points=None, **kwargs):
# Generate Delaunay tessellation from super class, then trim
super().__init__(shape=shape, num_points=num_points, **kwargs)
points = self['pore.coords']
conns = self['throat.conns']
# Find centroid of each pair of nodes
c = points[conns]
m = (c[:, 0, :] + c[:, 1, :])/2
# Find radius of circle connecting each pair of nodes
r = sp.sqrt(sp.sum((c[:, 0, :] - c[:, 1, :])**2, axis=1))/2
# Use KD-Tree to find distance to nearest neighbors
tree = sptl.cKDTree(points)
n = tree.query(x=m, k=1)[0]
# Identify throats whose centroid is not near an unconnected node
g = sp.around(n, decimals=5) == sp.around(r, decimals=5)
trim(self, throats=~g)
def __init__(self, shape=None, num_points=None, **kwargs):
# Clean-up input points
points = kwargs.pop('points', None)
points = self._parse_points(shape=shape,
num_points=num_points,
points=points)
# Initialize network object
super().__init__(shape=shape, points=points, **kwargs)
topotools.trim(network=self, pores=self.pores(['voronoi']))
pop = ['pore.voronoi', 'throat.voronoi', 'throat.interconnect',
'pore.delaunay', 'throat.delaunay']
for item in pop:
del self[item]
# Trim additional pores that are missed by the parent class's trimming
Ps = topotools.isoutside(coords=self['pore.coords'], shape=shape)
topotools.trim(network=self, pores=Ps)
def __init__(self, template, spacing=[1, 1, 1], **kwargs):
template = sp.atleast_3d(template)
if 'shape' in kwargs:
del kwargs['shape']
logger.warning('shape argument ignored, inferred from template')
super().__init__(shape=template.shape, spacing=spacing, **kwargs)
coords = sp.unravel_index(range(template.size), template.shape)
self['pore.template_coords'] = sp.vstack(coords).T
self['pore.template_indices'] = self.Ps
self['pore.drop'] = template.flatten() == 0
topotools.trim(network=self, pores=self.pores('drop'))
del self['pore.drop']
# remove labels pertaining to surface pores, then redo post-trim
self.clear(mode='labels')
self['pore.internal'] = True
self['throat.internal'] = True
topotools.find_surface_pores(self)
def test_check_network_health_isolated_pores_and_clusters(self):
net = op.network.Cubic(shape=[5, 5, 5])
# Create first isolated cluster
Ps = net['pore.coords'][:, 2] == 2.5
Ps = Ps*(net['pore.coords'][:, 1] > 2.5)
Ts = net.find_neighbor_throats(pores=Ps, mode='exclusive_or')
trim(network=net, throats=Ts)
# Create an isolated pore
Ts = net.find_neighbor_throats(pores=0)
trim(network=net, throats=Ts)
a = net.check_network_health()
# Ensure pore 0 counts as a cluster
assert len(a['disconnected_clusters']) == 3
# Ensure trim_pores has right length
assert len(a['trim_pores']) == 11
# Ensure 0 is listed in trim pores
assert 0 in a['trim_pores']
# Ensure 0 is also listed as an isolated pore
assert a['isolated_pores'] == 0
def make_1D_net(config):
sub = "GEOMETRY"
Nunit = config.getint(sub, "nunit_OneD")
spacing = config.getfloat(sub, "spacing_OneD")
pos_tabs = config.getint(sub, "pos_tabs")
neg_tabs = config.getint(sub, "neg_tabs")
net = op.network.Cubic([Nunit + 2, 2, 1], spacing)
net["pore.pos_cc"] = net["pore.front"]
net["pore.neg_cc"] = net["pore.back"]
T = net.find_neighbor_throats(net.pores("left"), mode="xnor")
tt.trim(net, throats=T)
T = net.find_neighbor_throats(net.pores("right"), mode="xnor")
tt.trim(net, throats=T)
pos_cc_Ts = net.find_neighbor_throats(net.pores("pos_cc"), mode="xnor")
neg_cc_Ts = net.find_neighbor_throats(net.pores("neg_cc"), mode="xnor")
pos_tab_nodes = net.pores()[net["pore.pos_cc"]][pos_tabs]
neg_tab_nodes = net.pores()[net["pore.neg_cc"]][neg_tabs]
net["pore.pos_tab"] = False
net["pore.neg_tab"] = False
net["pore.pos_tab"][pos_tab_nodes] = True
net["pore.neg_tab"][neg_tab_nodes] = True
net["throat.pos_cc"] = False
net["throat.neg_cc"] = False
net["throat.pos_cc"][pos_cc_Ts] = True
net["throat.neg_cc"][neg_cc_Ts] = True
net["throat.spm_resistor"] = True
net["throat.spm_resistor"][pos_cc_Ts] = False
net["throat.spm_resistor"][neg_cc_Ts] = False
net["throat.spm_resistor_order"] = -1
net["throat.spm_resistor_order"][net["throat.spm_resistor"]] = np.arange(
Nunit)
net["throat.spm_neg_inner"] = net["throat.spm_resistor"]
net["pore.free_stream"] = False
del net["pore.left"]
del net["pore.right"]
del net["pore.front"]
del net["pore.back"]
del net["pore.internal"]
del net["pore.surface"]
del net["throat.internal"]
del net["throat.surface"]
phase = op.phases.GenericPhase(network=net)
geo = op.geometry.GenericGeometry(network=net,
pores=net.Ps,
throats=net.Ts)
op.physics.GenericPhysics(network=net, phase=phase, geometry=geo)
net["pore.radial_position"] = net["pore.coords"][:, 0]
net["pore.arc_index"] = np.indices([Nunit + 2, 2, 1])[0].flatten()
net["pore.region_id"] = -1
net["pore.cell_id"] = -1
net["throat.arc_length"] = spacing
net["throat.electrode_height"] = spacing
# placeholder
net["pore.volume"] = 1.0
net["throat.area"] = 1.0
net["throat.length"] = 1.0
plot_topology(net)
return net.project, np.cumsum(net["throat.arc_length"])
def load(cls, path, prefix, network=None):
r"""
Load data from the \'dat\' files located in specified folder.
Parameters
----------
path : string
The full path to the folder containing the set of \'dat\' files.
prefix : string
The file name prefix on each file. The data files are stored
as \<prefix\>_node1.dat.
network : OpenPNM Network Object
If given then the data will be loaded on it and returned. If not
given, a Network will be created and returned.
Returns
-------
An OpenPNM Project containing a GenericNetwork holding all the data
"""
from pandas import read_table, DataFrame
net = {}
# Parse the link1 file
path = Path(path)
filename = Path(path.resolve(), prefix + '_link1.dat')
with open(filename, mode='r') as f:
link1 = read_table(filepath_or_buffer=f,
header=None,
skiprows=1,
sep=' ',
skipinitialspace=True,
index_col=0)
link1.columns = [
'throat.pore1', 'throat.pore2', 'throat.radius',
'throat.shape_factor', 'throat.total_length'
]
# Add link1 props to net
net['throat.conns'] = np.vstack(
(link1['throat.pore1'] - 1, link1['throat.pore2'] - 1)).T
net['throat.conns'] = np.sort(net['throat.conns'], axis=1)
net['throat.radius'] = np.array(link1['throat.radius'])
net['throat.shape_factor'] = np.array(link1['throat.shape_factor'])
net['throat.total_length'] = np.array(link1['throat.total_length'])
filename = Path(path.resolve(), prefix + '_link2.dat')
with open(filename, mode='r') as f:
link2 = read_table(filepath_or_buffer=f,
header=None,
sep=' ',
skipinitialspace=True,
index_col=0)
link2.columns = [
'throat.pore1', 'throat.pore2', 'throat.pore1_length',
'throat.pore2_length', 'throat.length', 'throat.volume',
'throat.clay_volume'
]
# Add link2 props to net
cl_t = np.array(link2['throat.length'])
net['throat.length'] = cl_t
net['throat.conduit_lengths.throat'] = cl_t
net['throat.volume'] = np.array(link2['throat.volume'])
cl_p1 = np.array(link2['throat.pore1_length'])
net['throat.conduit_lengths.pore1'] = cl_p1
cl_p2 = np.array(link2['throat.pore2_length'])
net['throat.conduit_lengths.pore2'] = cl_p2
net['throat.clay_volume'] = np.array(link2['throat.clay_volume'])
# ---------------------------------------------------------------------
# Parse the node1 file
filename = Path(path.resolve(), prefix + '_node1.dat')
with open(filename, mode='r') as f:
row_0 = f.readline().split()
num_lines = int(row_0[0])
array = sp.ndarray([num_lines, 6])
for i in range(num_lines):
row = f.readline()\
.replace('\t', ' ').replace('\n', ' ').split()
array[i, :] = row[0:6]
node1 = DataFrame(array[:, [1, 2, 3, 4]])
node1.columns = [
'pore.x_coord', 'pore.y_coord', 'pore.z_coord',
'pore.coordination_number'
]
# Add node1 props to net
net['pore.coords'] = np.vstack(
(node1['pore.x_coord'], node1['pore.y_coord'],
node1['pore.z_coord'])).T
# ---------------------------------------------------------------------
# Parse the node1 file
filename = Path(path.resolve(), prefix + '_node2.dat')
with open(filename, mode='r') as f:
node2 = read_table(filepath_or_buffer=f,
header=None,
sep=' ',
skipinitialspace=True,
index_col=0)
node2.columns = [
'pore.volume', 'pore.radius', 'pore.shape_factor',
'pore.clay_volume'
]
# Add node2 props to net
net['pore.volume'] = np.array(node2['pore.volume'])
net['pore.radius'] = np.array(node2['pore.radius'])
net['pore.shape_factor'] = np.array(node2['pore.shape_factor'])
net['pore.clay_volume'] = np.array(node2['pore.clay_volume'])
net['throat.area'] = ((net['throat.radius']**2) /
(4.0 * net['throat.shape_factor']))
net['pore.area'] = ((net['pore.radius']**2) /
(4.0 * net['pore.shape_factor']))
if network is None:
network = GenericNetwork()
network = cls._update_network(network=network, net=net)
# Use OpenPNM Tools to clean up network
# Trim throats connected to 'inlet' or 'outlet' reservoirs
trim1 = np.where(np.any(net['throat.conns'] == -1, axis=1))[0]
# Apply 'outlet' label to these pores
outlets = network['throat.conns'][trim1, 1]
network['pore.outlets'] = False
network['pore.outlets'][outlets] = True
trim2 = np.where(np.any(net['throat.conns'] == -2, axis=1))[0]
# Apply 'inlet' label to these pores
inlets = network['throat.conns'][trim2, 1]
network['pore.inlets'] = False
network['pore.inlets'][inlets] = True
# Now trim the throats
to_trim = np.hstack([trim1, trim2])
trim(network=network, throats=to_trim)
return network.project
def _trim_external_pores(self, shape):
r'''
'''
# Find all pores within the domain
Ps = topotools.isoutside(coords=self['pore.coords'], shape=shape)
self['pore.external'] = False
self['pore.external'][Ps] = True
# Find which internal pores are delaunay
Ps = (~self['pore.external'])*self['pore.delaunay']
# Find all pores connected to an internal delaunay pore
Ps = self.find_neighbor_pores(pores=Ps, include_input=True)
# Mark them all as keepers
self['pore.keep'] = False
self['pore.keep'][Ps] = True
# Trim all bad pores
topotools.trim(network=self, pores=~self['pore.keep'])
# Now label boundary pores
self['pore.boundary'] = False
self['pore.boundary'] = self['pore.delaunay']*self['pore.external']
# Label Voronoi pores on boundary
Ps = self.find_neighbor_pores(pores=self.pores('boundary'))
Ps = self['pore.voronoi']*self.tomask(pores=Ps)
self['pore.boundary'][Ps] = True
# Label Voronoi and interconnect throats on boundary
self['throat.boundary'] = False
Ps = self.pores('boundary')
Ts = self.find_neighbor_throats(pores=Ps, mode='xnor')
self['throat.boundary'][Ts] = True
# Trim throats between Delaunay boundary pores
Ps = self.pores(labels=['boundary', 'delaunay'], mode='xnor')
Ts = self.find_neighbor_throats(pores=Ps, mode='xnor')
topotools.trim(network=self, throats=Ts)
# Move Delaunay boundary pores to centroid of Voronoi facet
Ps = self.pores(labels=['boundary', 'delaunay'], mode='xnor')
for P in Ps:
Ns = self.find_neighbor_pores(pores=P)
Ns = Ps = self['pore.voronoi']*self.tomask(pores=Ns)
coords = sp.mean(self['pore.coords'][Ns], axis=0)
self['pore.coords'][P] = coords
self['pore.internal'] = ~self['pore.boundary']
Ps = self.pores('internal')
Ts = self.find_neighbor_throats(pores=Ps, mode='xnor')
self['throat.internal'] = False
self['throat.internal'][Ts] = True
# Label surface pores and throats between boundary and internal
Ts = self.throats(['boundary', 'internal'], mode='not')
self['throat.surface'] = False
self['throat.surface'][Ts] = True
surf_pores = self['throat.conns'][Ts].flatten()
surf_pores = sp.unique(surf_pores[~self['pore.boundary'][surf_pores]])
self['pore.surface'] = False
self['pore.surface'][surf_pores] = True
# Clean-up
del self['pore.external']
del self['pore.keep']
def load(cls, path, voxel_size=1, project=None):
r"""
Load data from a 3DMA-Rock extracted network. This format consists of
two files: 'rockname.np2th' and 'rockname.th2pn'. They should be
stored together in a folder which is referred to by the path argument.
These files are binary and therefore not human readable.
Parameters
----------
path : string
The location of the 'np2th' and 'th2np' files. This can be an
absolute path or relative to the current working directory.
network : OpenPNM Network Object
If an Network object is recieved, this method will add new data to
it but NOT overwrite anything that already exists. This can be
used to append data from different sources.
voxel_size : scalar
The resolution of the image on which 3DMA-Rock was run, in terms of
the linear length of eac voxel. The default is 1. This is used to
scale the voxel counts to actual dimension. It is recommended that
this value be in SI units [m] to work well with OpenPNM.
project : OpenPNM Project object
A GenericNetwork is created and added to the specified Project.
If no Project is supplied then one will be created and returned.
"""
net = {}
path = Path(path)
path = path.resolve()
for file in os.listdir(path):
if file.endswith(".np2th"):
np2th_file = os.path.join(path, file)
elif file.endswith(".th2np"):
th2np_file = os.path.join(path, file)
with open(np2th_file, mode='rb') as f:
[Np, Nt] = np.fromfile(file=f, count=2, dtype='u4')
net['pore.boundary_type'] = sp.ndarray([
Np,
], int)
net['throat.conns'] = np.ones([Nt, 2], int) * (-1)
net['pore.coordination'] = sp.ndarray([
Np,
], int)
net['pore.ID_number'] = sp.ndarray([
Np,
], int)
for i in range(0, Np):
ID = np.fromfile(file=f, count=1, dtype='u4')
net['pore.ID_number'][i] = ID
net['pore.boundary_type'][i] = np.fromfile(file=f,
count=1,
dtype='u1')
z = np.fromfile(file=f, count=1, dtype='u4')[0]
net['pore.coordination'][i] = z
att_pores = np.fromfile(file=f, count=z, dtype='u4')
att_throats = np.fromfile(file=f, count=z, dtype='u4')
for j in range(0, len(att_throats)):
t = att_throats[j] - 1
p = att_pores[j] - 1
net['throat.conns'][t] = [i, p]
net['throat.conns'] = np.sort(net['throat.conns'], axis=1)
net['pore.volume'] = np.fromfile(file=f, count=Np, dtype='u4')
nx = np.fromfile(file=f, count=1, dtype='u4')
nxy = np.fromfile(file=f, count=1, dtype='u4')
pos = np.fromfile(file=f, count=Np, dtype='u4')
ny = nxy / nx
ni = np.mod(pos, nx)
nj = np.mod(np.floor(pos / nx), ny)
nk = np.floor(np.floor(pos / nx) / ny)
net['pore.coords'] = np.array([ni, nj, nk]).T
with open(th2np_file, mode='rb') as f:
Nt = np.fromfile(file=f, count=1, dtype='u4')[0]
net['throat.area'] = np.ones([
Nt,
], dtype=int) * (-1)
for i in range(0, Nt):
ID = np.fromfile(file=f, count=1, dtype='u4')
net['throat.area'][i] = np.fromfile(file=f,
count=1,
dtype='f4')
# numvox = np.fromfile(file=f, count=1, dtype='u4')
att_pores = np.fromfile(file=f, count=2, dtype='u4')
nx = np.fromfile(file=f, count=1, dtype='u4')
nxy = np.fromfile(file=f, count=1, dtype='u4')
pos = np.fromfile(file=f, count=Nt, dtype='u4')
ny = nxy / nx
ni = np.mod(pos, nx)
nj = np.mod(np.floor(pos / nx), ny)
nk = np.floor(np.floor(pos / nx) / ny)
net['throat.coords'] = np.array([ni, nj, nk]).T
net['pore.internal'] = net['pore.boundary_type'] == 0
# Convert voxel area and volume to actual dimensions
net['throat.area'] = (voxel_size**2) * net['throat.area']
net['pore.volume'] = (voxel_size**3) * net['pore.volume']
if project is None:
project = Project(name=path)
network = GenericNetwork(project=project)
network = cls._update_network(network=network, net=net)
# Trim headless throats before returning
ind = np.where(network['throat.conns'][:, 0] == -1)[0]
trim(network=network, throats=ind)
return project
def import_data(cls,
path,
node_file="throats_cellsThroatsGraph_Nodes.txt",
graph_file="throats_cellsThroatsGraph.txt",
voxel_size=None):
r"""
Loads network data from an iMorph processed image stack
Parameters
----------
path : string
The path of the folder where the subfiles are held
node_file : string
The file that describes the pores and throats, the
default iMorph name is: throats_cellsThroatsGraph_Nodes.txt
graph_file : string
The file that describes the connectivity of the network, the
default iMorph name is: throats_cellsThroatsGraph.txt
voxel_size : float
Allows the user to define a voxel size different than what is
contained in the node_file. The value must be in meters.
Returns
-------
project : list
An OpenPNM project object containing a network and a geometry
object. The geometry-related data are automatically placed on the
geometry object using the ``Imported`` geometry class.
"""
path = Path(path)
node_file = os.path.join(path.resolve(), node_file)
graph_file = os.path.join(path.resolve(), graph_file)
# Parsing the nodes file
with open(node_file, "r") as file:
Np = np.fromstring(file.readline().rsplit("=")[1],
sep="\t",
dtype=int)[0]
vox_size = np.fromstring(
file.readline().rsplit(")")[1],
sep="\t",
)[0]
# Network always recreated to prevent errors
network = GenericNetwork(Np=Np, Nt=0)
# Define expected properies
network["pore.volume"] = np.nan
scrap_lines = [file.readline() for line in range(4)]
while True:
vals = file.readline().split("\t")
if len(vals) == 1:
break
network["pore.volume"][int(vals[0])] = float(vals[3])
if "pore." + vals[2] not in network.labels():
network["pore." + vals[2]] = False
network["pore." + vals[2]][int(vals[0])] = True
if voxel_size is None:
voxel_size = vox_size * 1.0e-6 # File stores value in microns
if voxel_size < 0:
raise Exception("Error - Voxel size must be specfied in " +
"the Nodes file or as a keyword argument.")
# Parsing the graph file
with open(graph_file, "r") as file:
# Define expected properties
network["pore.coords"] = np.zeros((Np, 3)) * np.nan
network["pore.types"] = np.nan
network["pore.color"] = np.nan
network["pore.radius"] = np.nan
network["pore.dmax"] = np.nan
network["pore.node_number"] = np.nan
# Scan file to get pore coordinate data
scrap_lines = [file.readline() for line in range(3)]
line = file.readline()
xmax = 0.0
ymax = 0.0
zmax = 0.0
node_num = 0
while line != "connectivity table\n":
vals = np.fromstring(line, sep="\t")
xmax = vals[1] if vals[1] > xmax else xmax
ymax = vals[2] if vals[2] > ymax else ymax
zmax = vals[3] if vals[3] > zmax else zmax
network["pore.coords"][int(vals[0]), :] = vals[1:4]
network["pore.types"][int(vals[0])] = vals[4]
network["pore.color"][int(vals[0])] = vals[5]
network["pore.radius"][int(vals[0])] = vals[6]
network["pore.dmax"][int(vals[0])] = vals[7]
network["pore.node_number"][int(vals[0])] = node_num
node_num += 1
line = file.readline()
# Scan file to get to connectivity data
scrap_lines.append(file.readline()) # Skip line
# Create sparse lil array incrementally build adjacency matrix
lil = sp.sparse.lil_matrix((Np, Np), dtype=int)
while True:
vals = np.fromstring(file.readline(), sep="\t", dtype=int)
if len(vals) <= 1:
break
lil.rows[vals[0]] = vals[2:].tolist()
lil.data[vals[0]] = np.ones(vals[1]).tolist()
# Fixing any negative volumes or distances so they are 1 voxel/micron
network["pore.volume"][np.where(network["pore.volume"] < 0)[0]] = 1.0
network["pore.radius"][np.where(network["pore.radius"] < 0)[0]] = 1.0
network["pore.dmax"][np.where(network["pore.dmax"] < 0)[0]] = 1.0
# Add adjacency matrix to OpenPNM network
conns = sp.sparse.triu(lil, k=1, format="coo")
network.update({"throat.all": np.ones(len(conns.col), dtype=bool)})
network["throat.conns"] = np.vstack([conns.row, conns.col]).T
network["pore.to_trim"] = False
network["pore.to_trim"][network.pores("*throat")] = True
Ts = network.pores("to_trim")
new_conns = network.find_neighbor_pores(pores=Ts, flatten=False)
extend(network=network, throat_conns=new_conns, labels="new_conns")
for item in network.props("pore"):
item = item.split(".")[1]
arr = np.ones_like(network["pore." + item])[0]
arr = np.tile(A=arr, reps=[network.Nt, 1]) * np.nan
network["throat." + item] = np.squeeze(arr)
network["throat." +
item][network.throats("new_conns")] = network["pore." +
item][Ts]
trim(network=network, pores=Ts)
# Setting up boundary pores
x_coord, y_coord, z_coord = np.hsplit(network["pore.coords"], 3)
network["pore.front_boundary"] = np.ravel(x_coord == 0)
network["pore.back_boundary"] = np.ravel(x_coord == xmax)
network["pore.left_boundary"] = np.ravel(y_coord == 0)
network["pore.right_boundary"] = np.ravel(y_coord == ymax)
network["pore.bottom_boundary"] = np.ravel(z_coord == 0)
network["pore.top_boundary"] = np.ravel(z_coord == zmax)
# Removing any pores that got classified as a boundary pore but
# Weren't labled a border_cell_face
ps = np.where(~np.in1d(network.pores("*_boundary"),
network.pores("border_cell_face")))[0]
ps = network.pores("*_boundary")[ps]
for side in ["front", "back", "left", "right", "top", "bottom"]:
network["pore." + side + "_boundary"][ps] = False
# Setting internal label
network["pore.internal"] = False
network["pore.internal"][network.pores("*_boundary",
mode="not")] = True
# Adding props to border cell face throats and from pores
Ts = np.where(
network["throat.conns"][:,
1] > network.pores("border_cell_face")[0] -
1)[0]
faces = network["throat.conns"][Ts, 1]
for item in network.props("pore"):
item = item.split(".")[1]
network["throat." + item][Ts] = network["pore." + item][faces]
network["pore.volume"][faces] = 0.0
# Applying unit conversions
# TODO: Determine if radius and dmax are indeed microns and not voxels
network["pore.coords"] = network["pore.coords"] * 1e-6
network["pore.radius"] = network["pore.radius"] * 1e-6
network["pore.dmax"] = network["pore.dmax"] * 1e-6
network["pore.volume"] = network["pore.volume"] * voxel_size**3
network["throat.coords"] = network["throat.coords"] * 1e-6
network["throat.radius"] = network["throat.radius"] * 1e-6
network["throat.dmax"] = network["throat.dmax"] * 1e-6
network["throat.volume"] = network["throat.volume"] * voxel_size**3
return network.project
def load(cls, path,
node_file="throats_cellsThroatsGraph_Nodes.txt",
graph_file="throats_cellsThroatsGraph.txt",
network=None, voxel_size=None, return_geometry=False):
r"""
Loads network data from an iMorph processed image stack
Parameters
----------
path : string
The path of the folder where the subfiles are held
node_file : string
The file that describes the pores and throats, the
default iMorph name is: throats_cellsThroatsGraph_Nodes.txt
graph_file : string
The file that describes the connectivity of the network, the
default iMorph name is: throats_cellsThroatsGraph.txt
network : OpenPNM Network Object
The OpenPNM Network onto which the data should be loaded. If no
network is supplied then an empty import network is created and
returned.
voxel_size : float
Allows the user to define a voxel size different than what is
contained in the node_file. The value must be in meters.
return_geometry : Boolean
If True, then all geometrical related properties are removed from
the Network object and added to a GenericGeometry object. In this
case the method returns a tuple containing (network, geometry). If
False (default) then the returned Network will contain all
properties that were in the original file. In this case, the user
can call the ```split_geometry``` method explicitly to perform the
separation.
Returns
-------
If no Network object is supplied then one will be created and returned.
If return_geometry is True, then a tuple is returned containing both
the network and a geometry object.
"""
#
path = Path(path)
node_file = os.path.join(path.resolve(), node_file)
graph_file = os.path.join(path.resolve(), graph_file)
# parsing the nodes file
with open(node_file, 'r') as file:
Np = sp.fromstring(file.readline().rsplit('=')[1], sep='\t',
dtype=int)[0]
vox_size = sp.fromstring(file.readline().rsplit(')')[1], sep='\t',)[0]
# network always recreated to prevent errors
network = GenericNetwork(Np=Np, Nt=0)
# Define expected properies
network['pore.volume'] = sp.nan
scrap_lines = [file.readline() for line in range(4)]
while True:
vals = file.readline().split('\t')
if len(vals) == 1:
break
network['pore.volume'][int(vals[0])] = float(vals[3])
if 'pore.'+vals[2] not in network.labels():
network['pore.'+vals[2]] = False
network['pore.'+vals[2]][int(vals[0])] = True
if voxel_size is None:
voxel_size = vox_size * 1.0E-6 # file stores value in microns
if voxel_size < 0:
raise(Exception('Error - Voxel size must be specfied in ' +
'the Nodes file or as a keyword argument.'))
# parsing the graph file
with open(graph_file, 'r') as file:
# Define expected properties
network['pore.coords'] = sp.zeros((Np, 3))*sp.nan
network['pore.types'] = sp.nan
network['pore.color'] = sp.nan
network['pore.radius'] = sp.nan
network['pore.dmax'] = sp.nan
network['pore.node_number'] = sp.nan
# Scan file to get pore coordinate data
scrap_lines = [file.readline() for line in range(3)]
line = file.readline()
xmax = 0.0
ymax = 0.0
zmax = 0.0
node_num = 0
while line != 'connectivity table\n':
vals = sp.fromstring(line, sep='\t')
xmax = vals[1] if vals[1] > xmax else xmax
ymax = vals[2] if vals[2] > ymax else ymax
zmax = vals[3] if vals[3] > zmax else zmax
network['pore.coords'][int(vals[0]), :] = vals[1:4]
network['pore.types'][int(vals[0])] = vals[4]
network['pore.color'][int(vals[0])] = vals[5]
network['pore.radius'][int(vals[0])] = vals[6]
network['pore.dmax'][int(vals[0])] = vals[7]
network['pore.node_number'][int(vals[0])] = node_num
node_num += 1
line = file.readline()
# Scan file to get to connectivity data
scrap_lines.append(file.readline()) # Skip line
# Create sparse lil array incrementally build adjacency matrix
lil = sp.sparse.lil_matrix((Np, Np), dtype=int)
while True:
vals = sp.fromstring(file.readline(), sep='\t', dtype=int)
if len(vals) <= 1:
break
lil.rows[vals[0]] = vals[2:]
lil.data[vals[0]] = sp.ones(vals[1])
# fixing any negative volumes or distances so they are 1 voxel/micron
network['pore.volume'][sp.where(network['pore.volume'] < 0)[0]] = 1.0
network['pore.radius'][sp.where(network['pore.radius'] < 0)[0]] = 1.0
network['pore.dmax'][sp.where(network['pore.dmax'] < 0)[0]] = 1.0
# Add adjacency matrix to OpenPNM network
conns = sp.sparse.triu(lil, k=1, format='coo')
network.update({'throat.all': sp.ones(len(conns.col), dtype=bool)})
network['throat.conns'] = sp.vstack([conns.row, conns.col]).T
network['pore.to_trim'] = False
network['pore.to_trim'][network.pores('*throat')] = True
Ts = network.pores('to_trim')
new_conns = network.find_neighbor_pores(pores=Ts, flatten=False)
extend(network=network, throat_conns=new_conns, labels='new_conns')
for item in network.props('pore'):
item = item.split('.')[1]
arr = sp.ones_like(network['pore.'+item])[0]
arr = sp.tile(A=arr, reps=[network.Nt, 1])*sp.nan
network['throat.'+item] = sp.squeeze(arr)
network['throat.'+item][network.throats('new_conns')] = \
network['pore.'+item][Ts]
trim(network=network, pores=Ts)
# setting up boundary pores
x_coord, y_coord, z_coord = sp.hsplit(network['pore.coords'], 3)
network['pore.front_boundary'] = sp.ravel(x_coord == 0)
network['pore.back_boundary'] = sp.ravel(x_coord == xmax)
network['pore.left_boundary'] = sp.ravel(y_coord == 0)
network['pore.right_boundary'] = sp.ravel(y_coord == ymax)
network['pore.bottom_boundary'] = sp.ravel(z_coord == 0)
network['pore.top_boundary'] = sp.ravel(z_coord == zmax)
# removing any pores that got classified as a boundary pore but
# weren't labled a border_cell_face
ps = sp.where(~sp.in1d(network.pores('*_boundary'),
network.pores('border_cell_face')))[0]
ps = network.pores('*_boundary')[ps]
for side in ['front', 'back', 'left', 'right', 'top', 'bottom']:
network['pore.'+side+'_boundary'][ps] = False
# setting internal label
network['pore.internal'] = False
network['pore.internal'][network.pores('*_boundary', mode='not')] = True
# adding props to border cell face throats and from pores
Ts = sp.where(network['throat.conns'][:, 1] >
network.pores('border_cell_face')[0] - 1)[0]
faces = network['throat.conns'][Ts, 1]
for item in network.props('pore'):
item = item.split('.')[1]
network['throat.'+item][Ts] = network['pore.'+item][faces]
network['pore.volume'][faces] = 0.0
# applying unit conversions
# TODO: Determine if radius and dmax are indeed microns and not voxels
network['pore.coords'] = network['pore.coords'] * 1e-6
network['pore.radius'] = network['pore.radius'] * 1e-6
network['pore.dmax'] = network['pore.dmax'] * 1e-6
network['pore.volume'] = network['pore.volume'] * voxel_size**3
network['throat.coords'] = network['throat.coords'] * 1e-6
network['throat.radius'] = network['throat.radius'] * 1e-6
network['throat.dmax'] = network['throat.dmax'] * 1e-6
network['throat.volume'] = network['throat.volume'] * voxel_size**3
return network.project
def load(cls, path, prefix, network=None):
r"""
Load data from the \'dat\' files located in specified folder.
Parameters
----------
path : string
The full path to the folder containing the set of \'dat\' files.
prefix : string
The file name prefix on each file. The data files are stored
as \<prefix\>_node1.dat.
network : OpenPNM Network Object
If given then the data will be loaded on it and returned. If not
given, a Network will be created and returned.
Returns
-------
An OpenPNM Project containing a GenericNetwork holding all the data
"""
net = {}
# ---------------------------------------------------------------------
# Parse the link1 file
path = Path(path)
filename = Path(path.resolve(), prefix+'_link1.dat')
with open(filename, mode='r') as f:
link1 = pd.read_table(filepath_or_buffer=f,
header=None,
skiprows=1,
sep=' ',
skipinitialspace=True,
index_col=0)
link1.columns = ['throat.pore1', 'throat.pore2', 'throat.radius',
'throat.shape_factor', 'throat.total_length']
# Add link1 props to net
net['throat.conns'] = sp.vstack((link1['throat.pore1']-1,
link1['throat.pore2']-1)).T
net['throat.conns'] = sp.sort(net['throat.conns'], axis=1)
net['throat.radius'] = sp.array(link1['throat.radius'])
net['throat.shape_factor'] = sp.array(link1['throat.shape_factor'])
net['throat.total_length'] = sp.array(link1['throat.total_length'])
# ---------------------------------------------------------------------
filename = Path(path.resolve(), prefix+'_link2.dat')
with open(filename, mode='r') as f:
link2 = pd.read_table(filepath_or_buffer=f,
header=None,
sep=' ',
skipinitialspace=True,
index_col=0)
link2.columns = ['throat.pore1', 'throat.pore2',
'throat.pore1_length', 'throat.pore2_length',
'throat.length', 'throat.volume',
'throat.clay_volume']
# Add link2 props to net
cl_t = sp.array(link2['throat.length'])
net['throat.length'] = cl_t
net['throat.conduit_lengths.throat'] = cl_t
net['throat.volume'] = sp.array(link2['throat.volume'])
cl_p1 = sp.array(link2['throat.pore1_length'])
net['throat.conduit_lengths.pore1'] = cl_p1
cl_p2 = sp.array(link2['throat.pore2_length'])
net['throat.conduit_lengths.pore2'] = cl_p2
net['throat.clay_volume'] = sp.array(link2['throat.clay_volume'])
# ---------------------------------------------------------------------
# Parse the node1 file
filename = Path(path.resolve(), prefix+'_node1.dat')
with open(filename, mode='r') as f:
row_0 = f.readline().split()
num_lines = int(row_0[0])
array = sp.ndarray([num_lines, 6])
for i in range(num_lines):
row = f.readline()\
.replace('\t', ' ').replace('\n', ' ').split()
array[i, :] = row[0:6]
node1 = pd.DataFrame(array[:, [1, 2, 3, 4]])
node1.columns = ['pore.x_coord', 'pore.y_coord', 'pore.z_coord',
'pore.coordination_number']
# Add node1 props to net
net['pore.coords'] = sp.vstack((node1['pore.x_coord'],
node1['pore.y_coord'],
node1['pore.z_coord'])).T
# ---------------------------------------------------------------------
# Parse the node1 file
filename = Path(path.resolve(), prefix+'_node2.dat')
with open(filename, mode='r') as f:
node2 = pd.read_table(filepath_or_buffer=f,
header=None,
sep=' ',
skipinitialspace=True,
index_col=0)
node2.columns = ['pore.volume', 'pore.radius', 'pore.shape_factor',
'pore.clay_volume']
# Add node2 props to net
net['pore.volume'] = sp.array(node2['pore.volume'])
net['pore.radius'] = sp.array(node2['pore.radius'])
net['pore.shape_factor'] = sp.array(node2['pore.shape_factor'])
net['pore.clay_volume'] = sp.array(node2['pore.clay_volume'])
net['throat.area'] = ((net['throat.radius']**2) /
(4.0*net['throat.shape_factor']))
net['pore.area'] = ((net['pore.radius']**2) /
(4.0*net['pore.shape_factor']))
if network is None:
network = GenericNetwork()
network = cls._update_network(network=network, net=net)
# Use OpenPNM Tools to clean up network
# Trim throats connected to 'inlet' or 'outlet' reservoirs
trim1 = sp.where(sp.any(net['throat.conns'] == -1, axis=1))[0]
# Apply 'outlet' label to these pores
outlets = network['throat.conns'][trim1, 1]
network['pore.outlets'] = False
network['pore.outlets'][outlets] = True
trim2 = sp.where(sp.any(net['throat.conns'] == -2, axis=1))[0]
# Apply 'inlet' label to these pores
inlets = network['throat.conns'][trim2, 1]
network['pore.inlets'] = False
network['pore.inlets'][inlets] = True
# Now trim the throats
to_trim = sp.hstack([trim1, trim2])
trim(network=network, throats=to_trim)
return network.project
def __init__(self,
shape,
spacing=1.0,
length=1.0,
psd_params={'distribution': 'norm',
'loc': None,
'scale': None},
name=None,
settings={},
**kwargs):
super().__init__(name=name)
self.settings.update(defsets)
self.settings.update(settings)
if isinstance(shape, int):
shape = sp.array([shape, shape, 2])
elif len(shape) == 2:
shape = sp.concatenate((sp.array(shape), [2]))
else:
raise Exception('shape not understood, must be int ' +
' or list of 2 ints')
if isinstance(spacing, float) or isinstance(spacing, int):
spacing = float(spacing)
self.settings['spacing'] = spacing
spacing = sp.array([spacing, spacing, length])
else:
raise Exception('spacing not understood, must be float')
net = Cubic(shape=shape, spacing=spacing, project=self, **kwargs)
Ps_top = net.pores('top')
Ps_bot = net.pores('bottom')
Ts = net.find_connecting_throat(P1=Ps_top, P2=Ps_bot)
Ts = net.tomask(throats=Ts)
trim(network=net, throats=~Ts)
geom = GenericGeometry(network=net, pores=net.Ps, throats=net.Ts)
geom.add_model(propname='throat.seed',
model=mods.geometry.throat_seed.random)
if psd_params['loc'] is None:
psd_params['loc'] = spacing[0]/2
if psd_params['scale'] is None:
psd_params['scale'] = spacing[0]/10
if psd_params['distribution'] in ['norm', 'normal', 'gaussian']:
geom.add_model(propname='throat.size_distribution',
seeds='throat.seed',
model=mods.geometry.throat_size.normal,
loc=psd_params['loc'], scale=psd_params['scale'])
elif psd_params['distribution'] in ['weibull']:
geom.add_model(propname='throat.size_distribution',
seeds='throat.seed',
model=mods.geometry.throat_size.weibull,
loc=psd_params['loc'],
scale=psd_params['scale'],
shape=psd_params['shape'])
else:
temp = psd_params.copy()
func = getattr(spst, temp.pop('distribution'))
psd = func.freeze(**temp)
geom.add_model(propname='throat.size_distribution',
seeds='throat.seed',
model=mods.geometry.throat_size.generic_distribution,
func=psd)
if sp.any(geom['throat.size_distribution'] < 0):
logger.warning('Given size distribution produced negative ' +
'throat diameters...these will be set to 0')
geom.add_model(propname='throat.diameter',
model=mods.misc.clip,
prop='throat.size_distribution',
xmin=1e-12, xmax=sp.inf)
if self.settings['adjust_psd'] is None:
if geom['throat.size_distribution'].max() > spacing[0]:
logger.warning('Given size distribution produced throats ' +
'larger than the spacing.')
elif self.settings['adjust_psd'] == 'clip':
geom.add_model(propname='throat.diameter',
model=mods.misc.clip,
prop='throat.size_distribution',
xmin=1e-12, xmax=spacing[0])
if geom['throat.size_distribution'].max() > spacing[0]:
logger.warning('Given size distribution produced throats ' +
'larger than the spacing...tube diameters ' +
'will be clipped between 0 and given spacing')
elif self.settings['adjust_psd'] == 'normalize':
tmin = max(1e-12, geom['throat.size_distribution'].min())
geom.add_model(propname='throat.diameter',
model=mods.misc.normalize,
prop='throat.size_distribution',
xmin=tmin, xmax=spacing[0])
if geom['throat.size_distribution'].max() > spacing[0]:
logger.warning('Given size distribution produced throats ' +
'larger than the spacing...tube diameters ' +
'will be normalized to fit given spacing')
else:
logger.warning('Settings not understood, ignoring')
geom.add_model(propname='pore.diameter',
model=mods.geometry.pore_size.from_neighbor_throats,
throat_prop='throat.diameter', mode='max')
geom.add_model(propname='pore.diameter',
model=mods.misc.constant, value=0.0)
geom.add_model(propname='throat.length',
model=mods.geometry.throat_length.ctc)
geom.add_model(propname='throat.area',
model=mods.geometry.throat_area.cylinder)
geom.add_model(propname='pore.area',
model=mods.misc.from_neighbor_throats,
throat_prop='throat.area')
geom.add_model(propname='pore.volume',
model=mods.misc.constant, value=0.0)
geom.add_model(propname='throat.volume',
model=mods.geometry.throat_volume.cylinder)
geom.regenerate_models()
# Now create a generic phase with physics models on it
phase = GenericPhase(network=net)
m = mods.physics.hydraulic_conductance.classic_hagen_poiseuille
phase.add_model(propname='throat.hydraulic_conductance',
model=m, regen_mode='deferred')
m = mods.physics.diffusive_conductance.classic_ordinary_diffusion
phase.add_model(propname='throat.diffusive_conductance',
model=m, regen_mode='deferred')
m = mods.physics.diffusive_conductance.classic_ordinary_diffusion
phase.add_model(propname='throat.entry_pressure',
model=m, regen_mode='deferred')
def load(cls, path, voxel_size=1, project=None):
r"""
Load data from a 3DMA-Rock extracted network. This format consists of
two files: 'rockname.np2th' and 'rockname.th2pn'. They should be
stored together in a folder which is referred to by the path argument.
These files are binary and therefore not human readable.
Parameters
----------
path : string
The location of the 'np2th' and 'th2np' files. This can be an
absolute path or relative to the current working directory.
network : OpenPNM Network Object
If an Network object is recieved, this method will add new data to
it but NOT overwrite anything that already exists. This can be
used to append data from different sources.
voxel_size : scalar
The resolution of the image on which 3DMA-Rock was run, in terms of
the linear length of eac voxel. The default is 1. This is used to
scale the voxel counts to actual dimension. It is recommended that
this value be in SI units [m] to work well with OpenPNM.
project : OpenPNM Project object
A GenericNetwork is created and added to the specified Project.
If no Project is supplied then one will be created and returned.
"""
net = {}
path = Path(path)
path = path.resolve()
for file in os.listdir(path):
if file.endswith(".np2th"):
np2th_file = os.path.join(path, file)
elif file.endswith(".th2np"):
th2np_file = os.path.join(path, file)
with open(np2th_file, mode='rb') as f:
[Np, Nt] = sp.fromfile(file=f, count=2, dtype='u4')
net['pore.boundary_type'] = sp.ndarray([Np, ], int)
net['throat.conns'] = sp.ones([Nt, 2], int)*(-1)
net['pore.coordination'] = sp.ndarray([Np, ], int)
net['pore.ID_number'] = sp.ndarray([Np, ], int)
for i in range(0, Np):
ID = sp.fromfile(file=f, count=1, dtype='u4')
net['pore.ID_number'][i] = ID
net['pore.boundary_type'][i] = sp.fromfile(file=f, count=1,
dtype='u1')
z = sp.fromfile(file=f, count=1, dtype='u4')[0]
net['pore.coordination'][i] = z
att_pores = sp.fromfile(file=f, count=z, dtype='u4')
att_throats = sp.fromfile(file=f, count=z, dtype='u4')
for j in range(0, len(att_throats)):
t = att_throats[j] - 1
p = att_pores[j] - 1
net['throat.conns'][t] = [i, p]
net['throat.conns'] = sp.sort(net['throat.conns'], axis=1)
net['pore.volume'] = sp.fromfile(file=f, count=Np, dtype='u4')
nx = sp.fromfile(file=f, count=1, dtype='u4')
nxy = sp.fromfile(file=f, count=1, dtype='u4')
pos = sp.fromfile(file=f, count=Np, dtype='u4')
ny = nxy/nx
ni = sp.mod(pos, nx)
nj = sp.mod(sp.floor(pos/nx), ny)
nk = sp.floor(sp.floor(pos/nx)/ny)
net['pore.coords'] = sp.array([ni, nj, nk]).T
with open(th2np_file, mode='rb') as f:
Nt = sp.fromfile(file=f, count=1, dtype='u4')[0]
net['throat.area'] = sp.ones([Nt, ], dtype=int)*(-1)
for i in range(0, Nt):
ID = sp.fromfile(file=f, count=1, dtype='u4')
net['throat.area'][i] = sp.fromfile(file=f, count=1,
dtype='f4')
numvox = sp.fromfile(file=f, count=1, dtype='u4')
att_pores = sp.fromfile(file=f, count=2, dtype='u4')
nx = sp.fromfile(file=f, count=1, dtype='u4')
nxy = sp.fromfile(file=f, count=1, dtype='u4')
pos = sp.fromfile(file=f, count=Nt, dtype='u4')
ny = nxy/nx
ni = sp.mod(pos, nx)
nj = sp.mod(sp.floor(pos/nx), ny)
nk = sp.floor(sp.floor(pos/nx)/ny)
net['throat.coords'] = sp.array([ni, nj, nk]).T
net['pore.internal'] = net['pore.boundary_type'] == 0
# Convert voxel area and volume to actual dimensions
net['throat.area'] = (voxel_size**2)*net['throat.area']
net['pore.volume'] = (voxel_size**3)*net['pore.volume']
if project is None:
project = Project(name=path)
network = GenericNetwork(project=project)
network = cls._update_network(network=network, net=net)
# Trim headless throats before returning
ind = sp.where(network['throat.conns'][:, 0] == -1)[0]
trim(network=network, throats=ind)
return project
def load(cls,
path,
node_file="throats_cellsThroatsGraph_Nodes.txt",
graph_file="throats_cellsThroatsGraph.txt",
network=None,
voxel_size=None,
return_geometry=False):
r"""
Loads network data from an iMorph processed image stack
Parameters
----------
path : string
The path of the folder where the subfiles are held
node_file : string
The file that describes the pores and throats, the
default iMorph name is: throats_cellsThroatsGraph_Nodes.txt
graph_file : string
The file that describes the connectivity of the network, the
default iMorph name is: throats_cellsThroatsGraph.txt
network : OpenPNM Network Object
The OpenPNM Network onto which the data should be loaded. If no
network is supplied then an empty import network is created and
returned.
voxel_size : float
Allows the user to define a voxel size different than what is
contained in the node_file. The value must be in meters.
return_geometry : Boolean
If True, then all geometrical related properties are removed from
the Network object and added to a GenericGeometry object. In this
case the method returns a tuple containing (network, geometry). If
False (default) then the returned Network will contain all
properties that were in the original file. In this case, the user
can call the ```split_geometry``` method explicitly to perform the
separation.
Returns
-------
If no Network object is supplied then one will be created and returned.
If return_geometry is True, then a tuple is returned containing both
the network and a geometry object.
"""
#
path = Path(path)
node_file = os.path.join(path.resolve(), node_file)
graph_file = os.path.join(path.resolve(), graph_file)
# parsing the nodes file
with open(node_file, 'r') as file:
Np = sp.fromstring(file.readline().rsplit('=')[1],
sep='\t',
dtype=int)[0]
vox_size = sp.fromstring(
file.readline().rsplit(')')[1],
sep='\t',
)[0]
# network always recreated to prevent errors
network = GenericNetwork(Np=Np, Nt=0)
# Define expected properies
network['pore.volume'] = sp.nan
scrap_lines = [file.readline() for line in range(4)]
while True:
vals = file.readline().split('\t')
if len(vals) == 1:
break
network['pore.volume'][int(vals[0])] = float(vals[3])
if 'pore.' + vals[2] not in network.labels():
network['pore.' + vals[2]] = False
network['pore.' + vals[2]][int(vals[0])] = True
if voxel_size is None:
voxel_size = vox_size * 1.0E-6 # file stores value in microns
if voxel_size < 0:
raise (Exception('Error - Voxel size must be specfied in ' +
'the Nodes file or as a keyword argument.'))
# parsing the graph file
with open(graph_file, 'r') as file:
# Define expected properties
network['pore.coords'] = sp.zeros((Np, 3)) * sp.nan
network['pore.types'] = sp.nan
network['pore.color'] = sp.nan
network['pore.radius'] = sp.nan
network['pore.dmax'] = sp.nan
network['pore.node_number'] = sp.nan
# Scan file to get pore coordinate data
scrap_lines = [file.readline() for line in range(3)]
line = file.readline()
xmax = 0.0
ymax = 0.0
zmax = 0.0
node_num = 0
while line != 'connectivity table\n':
vals = sp.fromstring(line, sep='\t')
xmax = vals[1] if vals[1] > xmax else xmax
ymax = vals[2] if vals[2] > ymax else ymax
zmax = vals[3] if vals[3] > zmax else zmax
network['pore.coords'][int(vals[0]), :] = vals[1:4]
network['pore.types'][int(vals[0])] = vals[4]
network['pore.color'][int(vals[0])] = vals[5]
network['pore.radius'][int(vals[0])] = vals[6]
network['pore.dmax'][int(vals[0])] = vals[7]
network['pore.node_number'][int(vals[0])] = node_num
node_num += 1
line = file.readline()
# Scan file to get to connectivity data
scrap_lines.append(file.readline()) # Skip line
# Create sparse lil array incrementally build adjacency matrix
lil = sp.sparse.lil_matrix((Np, Np), dtype=int)
while True:
vals = sp.fromstring(file.readline(), sep='\t', dtype=int)
if len(vals) <= 1:
break
lil.rows[vals[0]] = vals[2:]
lil.data[vals[0]] = sp.ones(vals[1])
# fixing any negative volumes or distances so they are 1 voxel/micron
network['pore.volume'][sp.where(network['pore.volume'] < 0)[0]] = 1.0
network['pore.radius'][sp.where(network['pore.radius'] < 0)[0]] = 1.0
network['pore.dmax'][sp.where(network['pore.dmax'] < 0)[0]] = 1.0
# Add adjacency matrix to OpenPNM network
conns = sp.sparse.triu(lil, k=1, format='coo')
network.update({'throat.all': sp.ones(len(conns.col), dtype=bool)})
network['throat.conns'] = sp.vstack([conns.row, conns.col]).T
network['pore.to_trim'] = False
network['pore.to_trim'][network.pores('*throat')] = True
Ts = network.pores('to_trim')
new_conns = network.find_neighbor_pores(pores=Ts, flatten=False)
extend(network=network, throat_conns=new_conns, labels='new_conns')
for item in network.props('pore'):
item = item.split('.')[1]
arr = sp.ones_like(network['pore.' + item])[0]
arr = sp.tile(A=arr, reps=[network.Nt, 1]) * sp.nan
network['throat.' + item] = sp.squeeze(arr)
network['throat.'+item][network.throats('new_conns')] = \
network['pore.'+item][Ts]
trim(network=network, pores=Ts)
# setting up boundary pores
x_coord, y_coord, z_coord = sp.hsplit(network['pore.coords'], 3)
network['pore.front_boundary'] = sp.ravel(x_coord == 0)
network['pore.back_boundary'] = sp.ravel(x_coord == xmax)
network['pore.left_boundary'] = sp.ravel(y_coord == 0)
network['pore.right_boundary'] = sp.ravel(y_coord == ymax)
network['pore.bottom_boundary'] = sp.ravel(z_coord == 0)
network['pore.top_boundary'] = sp.ravel(z_coord == zmax)
# removing any pores that got classified as a boundary pore but
# weren't labled a border_cell_face
ps = sp.where(~sp.in1d(network.pores('*_boundary'),
network.pores('border_cell_face')))[0]
ps = network.pores('*_boundary')[ps]
for side in ['front', 'back', 'left', 'right', 'top', 'bottom']:
network['pore.' + side + '_boundary'][ps] = False
# setting internal label
network['pore.internal'] = False
network['pore.internal'][network.pores('*_boundary',
mode='not')] = True
# adding props to border cell face throats and from pores
Ts = sp.where(
network['throat.conns'][:,
1] > network.pores('border_cell_face')[0] -
1)[0]
faces = network['throat.conns'][Ts, 1]
for item in network.props('pore'):
item = item.split('.')[1]
network['throat.' + item][Ts] = network['pore.' + item][faces]
network['pore.volume'][faces] = 0.0
# applying unit conversions
# TODO: Determine if radius and dmax are indeed microns and not voxels
network['pore.coords'] = network['pore.coords'] * 1e-6
network['pore.radius'] = network['pore.radius'] * 1e-6
network['pore.dmax'] = network['pore.dmax'] * 1e-6
network['pore.volume'] = network['pore.volume'] * voxel_size**3
network['throat.coords'] = network['throat.coords'] * 1e-6
network['throat.radius'] = network['throat.radius'] * 1e-6
network['throat.dmax'] = network['throat.dmax'] * 1e-6
network['throat.volume'] = network['throat.volume'] * voxel_size**3
return network.project
def __init__(self,
shape,
spacing=1.0,
length=1.0,
psd_params={
'distribution': 'norm',
'loc': None,
'scale': None
},
name=None,
settings={},
**kwargs):
super().__init__(name=name)
self.settings.update(defsets)
self.settings.update(settings)
if isinstance(shape, int):
shape = sp.array([shape, shape, 2])
elif len(shape) == 2:
shape = sp.concatenate((sp.array(shape), [2]))
else:
raise Exception('shape not understood, must be int ' +
' or list of 2 ints')
if isinstance(spacing, float) or isinstance(spacing, int):
spacing = float(spacing)
self.settings['spacing'] = spacing
spacing = sp.array([spacing, spacing, length])
else:
raise Exception('spacing not understood, must be float')
net = Cubic(shape=shape, spacing=spacing, project=self, **kwargs)
Ps_top = net.pores('top')
Ps_bot = net.pores('bottom')
Ts = net.find_connecting_throat(P1=Ps_top, P2=Ps_bot)
Ts = net.tomask(throats=Ts)
trim(network=net, throats=~Ts)
geom = GenericGeometry(network=net, pores=net.Ps, throats=net.Ts)
geom.add_model(propname='throat.seed',
model=mods.geometry.throat_seed.random)
if psd_params['loc'] is None:
psd_params['loc'] = spacing[0] / 2
if psd_params['scale'] is None:
psd_params['scale'] = spacing[0] / 10
if psd_params['distribution'] in ['norm', 'normal', 'gaussian']:
geom.add_model(propname='throat.size_distribution',
seeds='throat.seed',
model=mods.geometry.throat_size.normal,
loc=psd_params['loc'],
scale=psd_params['scale'])
elif psd_params['distribution'] in ['weibull']:
geom.add_model(propname='throat.size_distribution',
seeds='throat.seed',
model=mods.geometry.throat_size.weibull,
loc=psd_params['loc'],
scale=psd_params['scale'],
shape=psd_params['shape'])
else:
temp = psd_params.copy()
func = getattr(spst, temp.pop('distribution'))
psd = func.freeze(**temp)
geom.add_model(
propname='throat.size_distribution',
seeds='throat.seed',
model=mods.geometry.throat_size.generic_distribution,
func=psd)
if sp.any(geom['throat.size_distribution'] < 0):
logger.warning('Given size distribution produced negative ' +
'throat diameters...these will be set to 0')
geom.add_model(propname='throat.diameter',
model=mods.misc.clip,
prop='throat.size_distribution',
xmin=1e-12,
xmax=sp.inf)
if self.settings['adjust_psd'] is None:
if geom['throat.size_distribution'].max() > spacing[0]:
logger.warning('Given size distribution produced throats ' +
'larger than the spacing.')
elif self.settings['adjust_psd'] == 'clip':
geom.add_model(propname='throat.diameter',
model=mods.misc.clip,
prop='throat.size_distribution',
xmin=1e-12,
xmax=spacing[0])
if geom['throat.size_distribution'].max() > spacing[0]:
logger.warning('Given size distribution produced throats ' +
'larger than the spacing...tube diameters ' +
'will be clipped between 0 and given spacing')
elif self.settings['adjust_psd'] == 'normalize':
tmin = max(1e-12, geom['throat.size_distribution'].min())
geom.add_model(propname='throat.diameter',
model=mods.misc.normalize,
prop='throat.size_distribution',
xmin=tmin,
xmax=spacing[0])
if geom['throat.size_distribution'].max() > spacing[0]:
logger.warning('Given size distribution produced throats ' +
'larger than the spacing...tube diameters ' +
'will be normalized to fit given spacing')
else:
logger.warning('Settings not understood, ignoring')
geom.add_model(propname='pore.diameter',
model=mods.geometry.pore_size.from_neighbor_throats,
throat_prop='throat.diameter',
mode='max')
geom.add_model(propname='pore.diameter',
model=mods.misc.constant,
value=0.0)
geom.add_model(propname='throat.length',
model=mods.geometry.throat_length.ctc)
geom.add_model(propname='throat.area',
model=mods.geometry.throat_area.cylinder)
geom.add_model(propname='pore.area',
model=mods.misc.from_neighbor_throats,
throat_prop='throat.area')
geom.add_model(propname='pore.volume',
model=mods.misc.constant,
value=0.0)
geom.add_model(propname='throat.volume',
model=mods.geometry.throat_volume.cylinder)
geom.regenerate_models()
# Now create a generic phase with physics models on it
phase = GenericPhase(network=net)
m = mods.physics.hydraulic_conductance.classic_hagen_poiseuille
phase.add_model(propname='throat.hydraulic_conductance',
model=m,
regen_mode='deferred')
m = mods.physics.diffusive_conductance.classic_ordinary_diffusion
phase.add_model(propname='throat.diffusive_conductance',
model=m,
regen_mode='deferred')
m = mods.physics.diffusive_conductance.classic_ordinary_diffusion
phase.add_model(propname='throat.entry_pressure',
model=m,
regen_mode='deferred')